Traditional design methods are generally unsuitable for optimally designing organic shapes made possible by additive manufacturing. In this study, a simple Genetic Algorithm (GA) optimisation routine was developed for a relevant engineering design problem – the optimisation of thickness distribution for a crenelated fuselage skin panel. The basis for this optimisation is the damage tolerance behaviour of the panel in the presence of a fatigue crack. The results demonstrated that crossover and mutation are inherently more similar than expected, thus questioning whether it is not more important to design a set of search heuristics through better understanding of the fitness space, rather than the application of a flawed, nature-inspired standard crossover and random mutation. Through these insights, this research contributed to ongoing research in understanding GAs, which, if better understood, could assist engineers in finding improved designs of additively manufactured components.